Jointly analyzing freeway primary and secondary crash severity using a copula-based approach

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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  • Helai Huang
  • Xizhi Ding
  • Chen Yuan
  • Xinyuan Liu
  • Jinjun Tang

Related Research Unit(s)


Original languageEnglish
Article number106911
Journal / PublicationAccident Analysis and Prevention
Online published2 Dec 2022
Publication statusPublished - Feb 2023


A copula-based model is developed in this study to jointly model the severity of freeway primary crashes and secondary crashes. The copula-based model can concurrently account for the severity levels in the crash and the correlation among primary-secondary crash pairs’ severity. The model comprehensively considers a series of explanation variables, including temporal characteristics, crash characteristics, roadway characteristics and real-traffic conditions, and is estimated using traffic crash data from 2016 through 2019 for Los Angeles County, California. The proposed copula model is then contrasted with the traditional binary probit model and the results show a remarkable advantage of the copula model, which is evidenced by better fitting performance. It is found that weather, whether towed away, unsafe speed, collision type, road condition, terrain, road weaving and truck involvement have significant impact on primary crash severity propensity and collision type, road width, road condition, traffic volume and vehicle speed have significant impact on secondary crash severity propensity. In light of the findings, a number of countermeasures are proposed to mitigate freeway crashes, including emergency services, vehicle and roadway engineering, traffic law enforcement and driver education.

Research Area(s)

  • Injury severity, Joe copula, Primary crash, Real-time traffic condition, Secondary crash